Lead Site Reliability Engineer

Lead Site Reliability Engineer# Careers at Little Caesars## Lead Site Reliability Engineer Apply:
Detroit, MI:
Full time:
Posted Yesterday:
R9599
** Job Summary**:

The Lead Site Reliability Engineer ensures our cloud-native ecommerce platform is reliable, scalable, secure, and cost-efficient, and that it performs at its peak capability at all times. This hands-on technical leader supervises our cloud administrators and platform engineers and sets direction across Kubernetes, CI/CD pipelines, infrastructure and configuration as code, observability, cloud hygiene, Fin Ops, and our growing AI platform. The Lead Site Reliability Engineer partners with development teams to define service level objectives, conduct production readiness reviews, manage releases, and troubleshoot complex issues, and uses AI to accelerate coding, research, and automation.

This role interacts with functional areas across all levels of the organization.
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* Key Responsibilities:

*** Supervise, mentor, and develop a team of cloud administrators and platform engineers. Set priorities, lead daily standups, and ensure work and ticket queues are balanced and resolved in a timely manner.
* Lead incident response and troubleshooting across the stack, act as an escalation point, and run blameless post-incident reviews that drive short-term and long-term fixes and eliminate repeat occurrences. Continuously assess system risks and improve internal processes and controls to prevent downtime.
* Own release management, ensuring scheduled changes go out as planned through automated, low-risk rollouts and fast, reliable rollback. Participate in early AM deployment calls as needed.
* Partner with development teams to define service level objectives (SLOs), service level indicators (SLIs), and error budgets, and conduct production readiness reviews to ensure new and changed services meet standards for reliability, scalability, security, observability, and supportability before launch.
* Design, build, and operate large-scale, distributed, fault-tolerant cloud-native systems on Kubernetes across public cloud providers such as Azure, AWS, or GCP, including capacity planning, load testing, and performance tuning to keep systems ahead of demand.
* Build and maintain CI/CD pipelines and Git Ops workflows (e.g., Azure Dev Ops), and manage infrastructure and configuration as code (e.g., Terraform, Ansible) to deliver consistent, repeatable, self-service environments and to detect and correct configuration drift.
* Establish and mature observability, including metrics, logs, traces, dashboards, and actionable alerting, to measure availability, latency, and overall system health. Provide routine reporting to senior management on reliability, SLO attainment, incidents, cloud spend, ticket trends, and project status.
* Drive Fin Ops and cloud hygiene practices in partnership with engineering and finance, including cost visibility, tagging and allocation, rightsizing, resource lifecycle management, patching, decommissioning of unused resources, and governance guardrails.
* Help build and run our AI platform, and operate and secure API and AI gateways, providing engineering teams with reliable, governed, and cost-aware access to AI models and services, including traffic management, authentication, rate limiting, and usage visibility.
* Automate operational tasks and eliminate toil using Bash, Python, and AI tools for coding, research, and automation, and champion the responsible use of AI across the team to accelerate delivery.
** Required

Knowledge, Skills and Abilities:

*** Bachelor’s degree in Computer Science or a similar area. Relevant experience may be considered in lieu of a degree.
* Minimum of four (4) years of experience in site reliability engineering, platform engineering, Dev Ops, or Linux systems administration.
* Hands-on experience running production workloads on Kubernetes and at least one major public cloud provider (Azure, AWS, or GCP).
* Strong experience with infrastructure as code and configuration management (e.g., Terraform, Ansible).
* Experience building and maintaining CI/CD pipelines and Git Ops-based delivery (e.g., Azure Dev Ops).
* Proficiency in scripting and automation using Bash and Python.
* Experience implementing observability (metrics, logging, tracing, and alerting) and defining SLOs, SLIs, and error budgets.
* Working knowledge of networking fundamentals, high availability, load balancing, and API gateways.
* Practical experience using AI tools to accelerate…